Autonomous robotic systems include navigation and object manipulation applications that employ physical object detection and recognition. A given autonomous robotic system may be called upon to operate in a wide variety of both indoor and outdoor environments which may be either structured (e.g., controlled) or unstructured (e.g., uncontrolled) and can have varying levels of complexity. As such, robust physical object detection and recognition across a wide variety of object types/classes/categories are needed in order for the robotic system to be able to interact with its environment in a safe and effective manner. This is generally accomplished by using a large set of labeled object data to train the robotic system's navigation and object manipulation applications, where the size of this dataset can be quite large for unstructured environments having a high level of complexity.
Additionally, the World Wide Web currently hosts billions of webpages which collectively currently host approximately one trillion images and these numbers continue to grow at a rapid pace. Various efforts are ongoing to label more of these images with meaningful data.